Lightweight Research on Anchor Machinery and Chain Wheel Assembly

In order to achieve more scientific design of the Anchor chain wheel and reduce material waste, pre-stressed modal analysis method was combined with multi-objective optimization algorithm to optimize the structure of the reduction Anchor chain wheel basic body. The model was simplified and parameterized and the maximum stress and equivalent stiffness under different parameter size combinations were obtained through finite element analysis. Separately, genetic clustering method, neural network method, and Kriging method were used to construct the response surface function. Through error verification and comparison, it was found that the Kriging method was more suitable for the Anchor chain wheel. Additionally, the lightweight design of the anchor chain wheel was achieved by comparing initial values with results from two optimization algorithms, NLPQL and MOGA.The results shows that under the condition of the NLPQL algorithm, the anchor chain wheel weight can be reduced by 7.1%, while maintaining the maximum stress and maximum deformation from increasing, and the optimization effect is significant.